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Reinforcement Learning Research Engineer – Exploration & Decision Intelligence (m/w/d)
Autonomous Teaming›
📍Munich (DEU)
unknownEngineering & Tech
Posted 1mo ago · via personio
Apply on personio→Job Description
What we offer
- Opportunity to work on a new solution from scratch in a technical complex environment
- Work in an international, agile, cross-functional team creating the future of autonomous systems
- Grow your career in a expanding and ambitious engineering team
- Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy
- Benefit from a steep learning curve and continuous development
- Enjoy team events and a strong, collaborative culture
Your mission
Build real autonomous systems that operate in the real world, not in the lab.
Join our engineering team of a new product and help build the core autonomy that powers our next generation robotic systems used for defense and mission-critical operations. You will design, implement, and harden robotic software that must perform under real operational conditions - outdoors, under uncertainty, with real consequences. Your work will directly shape the reliability, safety, and tactical capability of the systems we deliver.
- Research and prototype novel RL algorithms (e.g. exploration, POMDPs, multi-agent systems)
- Define, design and implement use-cases for DRL on edge devices
- Translate theory into scalable systems with support from our engineering teams
- Collaborate with simulation, autonomy and AI infrastructure teams
- Develop decision-making for intelligent behavior and architectures
Your profile
- Deep knowledge of RL theory and practice: policy gradients, value iteration, Q-learning, etc.
- Experience with ML training in physics based simulation (Gazebo, IsaacSim, Mujoco, Carla, etc.).
- Strong Programming proficiency (Python, C/C++).
- Comfortable with ML tooling and maintaining ML pipelines (Pytorch Lightning, MlFlow, etc.).
- Have experience with deploying ML methods to physical devices.
- Experience with version control (git).
- Familiarity with statistics, evaluation methods and experiment design.
- You think rigorously and build practically.
Nice to have
- PhD in Reinforcement Learning, Robot Engineering or equivalent with experience in deploying developed methods to real robots.
- OR masters degree in relevant field with extensive experience in RL.
- Experience with sensor based end-to-end ML architectures.
- Familiar with Transformers, Attention, Graphs, VLAs and other modern day ML building blocks.
- Publications at NeurIPS, ICLR, ICML, ICRA, IROS, etc. are a plus
- Experience with robotics middleware (ISAAC, ROS/ROS2, etc.)
Why us?
- Willingness to travel
- Citizenship of NATO member country or closed allied are mandatory
Details
- Department
- Engineering & Tech
- Work Type
- unknown
- Locations
- Munich (DEU)
- Posted
- April 8, 2026
- Source
- personio